{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 第 1 章：深度学习基础"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Python 入门"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Python 基础知识"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 数据类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "int"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "float"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(2.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type('python')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "bool"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "bool"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 数学运算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 + 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 - 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 * 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 / 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = 1       # 赋值\n",
    "x = 1.5     # 再次赋值\n",
    "y = 2.5\n",
    "x + y       # 计算"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 列表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 'python']\n"
     ]
    }
   ],
   "source": [
    "a = [1, 2, 3, 'python']\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "a[-1] = 4   # 最后一个元素赋值4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4]\n"
     ]
    }
   ],
   "source": [
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = [1, 2, 3, 4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0:1]      # 包含的索引：0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0:3]      # 包含的索引：0,1,2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:-1]      # 包含的索引：0,1,2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2, 3, 4]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[1:]       # 包含的索引：1,2,3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 字典"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "user = {'name': 'Will'}     # 生成字典"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Will'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user['name']                # 访问元素"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "user['age'] = 29            # 添加新元素"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': 'Will', 'age': 29}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### if 语句"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "He is busy now\n"
     ]
    }
   ],
   "source": [
    "busy = True\n",
    "if busy:\n",
    "    print('He is busy now')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### for 循环"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n"
     ]
    }
   ],
   "source": [
    "for i in [0,1,2]:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n"
     ]
    }
   ],
   "source": [
    "for i in range(3):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sign(x):\n",
    "    if x > 0:\n",
    "        return 'positive'\n",
    "    elif x < 0:\n",
    "        return 'negative'\n",
    "    else:\n",
    "        return 'zero'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "negative\n",
      "zero\n",
      "positive\n"
     ]
    }
   ],
   "source": [
    "for x in [-1, 0, 1]:\n",
    "    print(sign(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def greet(name, loud=False):\n",
    "    if loud:\n",
    "        print('HELLO, %s!' % name.upper())\n",
    "    else:\n",
    "        print('hello, %s!' % name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello, will!\n"
     ]
    }
   ],
   "source": [
    "greet('will')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HELLO, WILL!\n"
     ]
    }
   ],
   "source": [
    "greet('will', loud=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 类 Class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Greeter(object):\n",
    "    def __init__(self, name):\n",
    "        self.name = name        # 实例变量\n",
    "\n",
    "    # 定义实例方法\n",
    "    def greet(self, loud=False):\n",
    "        if loud:\n",
    "            print('HELLO, %s' % self.name.upper())\n",
    "        else:\n",
    "            print('hello, %s' % self.name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "g = Greeter('will')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello, will\n"
     ]
    }
   ],
   "source": [
    "g.greet()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HELLO, WILL\n"
     ]
    }
   ],
   "source": [
    "g.greet(loud=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "类的继承"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Know(Greeter):\n",
    "    \"\"\"子类Know继承于父类Greeter\"\"\"\n",
    "    def meet(self):\n",
    "        print('Nice to meet you!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "k = Know('will')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello, will\n"
     ]
    }
   ],
   "source": [
    "k.greet()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nice to meet you!\n"
     ]
    }
   ],
   "source": [
    "k.meet()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### NumPy 矩阵运算"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 导入 NumPy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### NumPy 数组"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([1, 2, 3])\n",
    "print(a)\n",
    "type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = np.array([[1, 2, 3], [4, 5, 6]])\n",
    "print(b)\n",
    "type(b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### NumPy 的数学运算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.array([1, 2, 3])\n",
    "y = np.array([2, 4, 6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 6, 9])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x + y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1, -2, -3])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x - y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2,  8, 18])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x * y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.5, 0.5, 0.5])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x / y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array([1, 2, 3, 4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2])"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([10,  2,  3,  4])"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0] = 10\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### NumPy 广播机制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3, 4],\n",
       "       [5, 6]])"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.array([[1, 2], [3, 4]])\n",
    "b = 2\n",
    "A + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3, 4],\n",
       "       [5, 6],\n",
       "       [7, 8]])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.array([[1, 2], [3, 4], [5, 6]])\n",
    "B = np.array([2, 2])\n",
    "A + B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3, 3],\n",
       "       [4, 4]])"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.array([[1], [2]])\n",
    "B = np.array([[2, 2]])\n",
    "A + B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2]\n",
      "[[1 2]]\n"
     ]
    }
   ],
   "source": [
    "a = np.array([1,2])\n",
    "print(a)\n",
    "a = a.reshape(1, -1)\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### NumPy 矩阵运算速度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25041.70479379088\n",
      "for loop:58.15482139587402ms\n",
      "25041.70479379091\n",
      "Vectorized:13.560771942138672ms\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import time\n",
    "\n",
    "a = np.random.rand(100000)\n",
    "b = np.random.rand(100000)\n",
    "\n",
    "c = 0\n",
    "tic = time.time()\n",
    "for i in range(100000):\n",
    "    c += a[i]*b[i]\n",
    "toc = time.time()\n",
    "\n",
    "print(c)\n",
    "print(\"for loop:\" + str(1000*(toc-tic)) + \"ms\")\n",
    "\n",
    "c = 0\n",
    "tic = time.time()\n",
    "c = np.dot(a,b)\n",
    "toc = time.time()\n",
    "\n",
    "print(c)\n",
    "print(\"Vectorized:\" + str(1000*(toc-tic)) + \"ms\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Matplotlib 绘图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 绘制图形 plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 导入库函数\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 生成数据\n",
    "x = np.arange(0, 4 * np.pi, 0.1)\n",
    "y = np.sin(x)\n",
    "\n",
    "# 绘图\n",
    "plt.plot(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 导入库函数\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 生成数据\n",
    "x = np.arange(0, 4 * np.pi, 0.1)\n",
    "y_sin = np.sin(x)\n",
    "y_cos = np.cos(x)\n",
    "\n",
    "# 绘图\n",
    "plt.plot(x, y_sin)\n",
    "plt.plot(x, y_cos, '--')\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('y')\n",
    "plt.title('Sin and Cos')\n",
    "plt.legend(['Sin', 'Cos'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 绘制散点图 scatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 生成数据\n",
    "x = np.random.randn(200)\n",
    "y = np.random.randn(200)\n",
    "# 绘制散点图\n",
    "plt.scatter(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 生成数据\n",
    "x1 = np.random.randn(200)\n",
    "y1 = np.random.randn(200)\n",
    "x2 = np.random.randn(200) + 3\n",
    "y2 = np.random.randn(200) + 3\n",
    "# 绘制散点图\n",
    "plt.scatter(x1, y1, marker='o')\n",
    "plt.scatter(x2, y2, marker='s')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 显示图像 imshow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.image import imread\n",
    "\n",
    "# 读取图像\n",
    "img = imread('./datasets/ch01/cat.jpg')\n",
    "\n",
    "# 显示图像\n",
    "plt.imshow(img)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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